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Open AccessVol 11 No 2Research articleAdherence with urate-lowering therapies for the treatment of goutLeslie R Harrold1,2,3, Susan E Andrade1,2,3, Becky A Briesacher1,2, Marsha A Raebel3,4, Hassan Fouayzi1, Robert A Yood1,5 and Ira S Ockene2

1Department of Medicine, the Meyers Primary Care Institute, 425 North Lake Avenue Worcester, MA 01605, USA2Department of Medicine, University of Massachusetts Medical School, 377 Plantation Street Worcester, MA 01605, USA3The HMO Research Network Center for Education and Research in Therapeutics, Department of Medicine, University of Massachusetts Medical School, 377 Plantation Street Worcester, MA 01605, USA4Department of Research, Kaiser Permanente, Colorado Institute for Health Research, PO Box 378066 Denver, CO 80237-8066, USA5Department of Medicine, Fallon Clinic, 425 North Lake Avenue Worcester, MA 01605, USA

Corresponding author: Leslie R Harrold, [email protected]

Received: 17 Nov 2008 Revisions requested: 7 Jan 2009 Revisions received: 5 Feb 2009 Accepted: 27 Mar 2009 Published: 27 Mar 2009

Arthritis Research & Therapy 2009, 11:R46 (doi:10.1186/ar2659)This article is online at: http://arthritis-research.com/content/11/2/R46© 2009 Harrold et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Introduction Adherence to urate-lowering drugs (ULDs) has notbeen well evaluated among those with gout. Our aim was toassess the level and determinants of non-adherence with ULDsprescribed for gout.

Methods We identified persons using two integrated deliverysystems aged 18 years or older with a diagnosis of gout whoinitiated use of allopurinol, probenecid or sulfinpyrazone from 1January 2000 to 30 June 2006. Non-adherence was measuredusing the medication possession ratio (MPR) over the first yearof therapy and defined as an MPR < 0.8. Descriptive statisticswere calculated and logistic regression was used to estimatethe strength of the association between patient characteristicsand non-adherence.

Results A total of 4,166 gout patients initiated ULDs; 97%received allopurinol. Median MPR for any ULD use was 0.68(interquartile range (IQR) 0.64). Over half of the patients (56%)

were non-adherent (MPR < 0.8). In adjusted analyses,predictors of poor adherence included younger age (odds ratio(OR) 2.43, 95% confidence interval (CI) 1.86 to 3.18 for ages<45 and OR 1.44, 95% CI 1.08 to 1.93 for ages 45 to 49),fewer comorbid conditions (OR 1.46, 95% CI 1.20 to 1.77), noprovider visits for gout prior to urate-lowering drug initiation (OR1.28, 95% CI 1.05 to 1.55), and use of non-steroidal anti-inflammatory drugs in the year prior to urate-lowering druginitiation (OR 1.15, 95% CI 1.00 to 1.31).

Conclusions Non-adherence amongst gout patients initiatingULDs is exceedingly common, particularly in younger patientswith less comorbidity and no provider visits for gout prior to ULDinitiation. Providers should be aware of the magnitude of non-adherence with ULDs.

IntroductionGout is a common inflammatory arthropathy affecting up to 5million Americans, and yet little is known regarding the dynam-ics of chronic medication use in these patients [1]. Both recur-rent and tophaceous gout require sustained treatment withurate-lowering drugs (ULDs) to reduce the frequency of acutegouty attacks and prevent urate nephropathy, uric acid neph-rolithiasis, and the deposition of tophi: a common cause ofprogressive joint damage, deformity and functional impairment[2,3]. Chronic use of ULDs is necessary for lowering and main-

taining serum uric acid levels to a target threshold of <6.0 mg/dl, as this is associated with fewer gout flares, reduction oftophus area, and depletion of urate crystal stores in synovialtissues [4-7].

Surprisingly little is known about how patients with gout man-age their ULD therapy even though adherence is critical forpreventing the painful and damaging effects of the disease[8,9]. A recent review of the literature detected very few stud-ies on this topic [10-13]. In addition, the studies varied in

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CERTs: Center for Education and Research on Therapeutics; ICD-9: International Disease Classification; MPR: medication possession ratio; NDC: national drug codes; NSAID: non-steroidal anti-inflammatory drug; ULDs: urate-lowering drugs; VDW: Virtual Data Warehouse.

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terms of study design, study populations, and definitions ofadherence. A recent study comparing medication non-adher-ence across seven common chronic conditions such as hyper-tension, osteoporosis and diabetes mellitus found adherencewas lowest with gout [8]. Interestingly, predictors of adher-ence varied by condition. For example, younger age was asso-ciated with lower adherence in the treatment ofhypothyroidism and diabetes but not in seizure disorders.Additionally, as comorbidity burden increased, adherence toosteoporosis treatment decreased whereas adherence tomedications used to treat hypertension and hypercholestero-lemia increased.

While non-adherence in certain other chronic conditions (forexample, hyperlipidemia) may not be associated with short-term consequences, interruptions in ULD use can trigger orprolong acute gout attacks [3,4]. The most recent publicationlooking at predictors of adherence in gout patients wasfocused on the elderly (mean age of the study population was79), and the overwhelming majority of patients were women[13]. That study population is not representative of patientstypically followed in an outpatient medical practice. Therefore,more investigation in the rates and causes of non-adherencein the treatment of gout is necessary, particularly in men andyounger populations. Specifically, the objective of this studywas to analyze the rates and predictors of non-adherence withULDs in a representative sample of gout patients. We hypoth-esized that patients with more frequent gout attacks would bemore adherent.

Materials and methodsSetting and datasetTwo health care delivery systems involved in the Health Main-tenance Organizations (HMO) Research Network Center forEducation and Research on Therapeutics (CERTs) partici-pated in this study [14]. The two systems are located in theNortheast and Rocky Mountain regions of the USA, with acombined population of approximately 650,000 (2006 fig-ures). We identified the study cohort using the Virtual DataWarehouse (VDW), a previously-developed mechanism usedto produce comparable data across participating health plans[15]. The VDW uses standardized file definitions, uniform datadictionaries for each content area, and common formats foreach data element. These common file structures enable ana-lysts at each site to write programs to extract and/or analyzedata at all participating sites. For this study, the analytic data-set included computerized information on utilization of healthcare services including membership, pharmacy dispensingdata, and selected hospital and ambulatory diagnoses andprocedures for all enrollees of the health plans from 1 January1999 to 30 June 2007. Institutional review boards at each par-ticipating organization approved this study.

Study population and designWe identified members from the dataset who had an Interna-tional Disease Classification, version 9 (ICD-9) code for a goutdiagnosis (codes 274.XX), were aged 18 years or older at thetime of the first ULD dispensing, were dispensed a ULD (allop-urinol, probenecid or sulfinpyrazone) between 1 January 2000and 30 June 2006 and were continuously enrolled in thehealth plan with drug coverage during the period 12 monthsprior to and 12 months following the first ULD dispensing. Ouranalysis focused on new users of therapy, which was definedas no dispensing of a ULD in the prior 6 months.

Adherence measureWe used the medication possession ratio (MPR) to measureadherence [16]. The MPR was calculated as the days supplyof medication dispensed during the follow-up year divided bythe number of days in the year and is a reliable measure ofadherence [17]. The MPR was determined based on phar-macy dispensing records, including the number of days sup-plied. Use of the MPR allowed comparisons with other studieswho used similar methods in examining adherence to ULDs[11-13]. As has been performed in other prior studies, theMPR was dichotomized at 80% in multivariable analyses, withan MPR of <80% considered non-adherence [11-13].

Covariates and measuresPatient characteristics were assessed, including those covari-ates identified as potential correlates of adherence based onprevious studies [11-13,18]. These included demographicfactors (age and sex), health care utilization (visits to providersfor gout both prior to and after ULD initiation, all provider visitsprior to ULD initiation, and number of hospitalizations prior toULD initiation), specific comorbidities, other medications usedto treat symptomatic gout, and medications that can triggergout. Age (as of first ULD dispensing) and sex were ascer-tained from the demographic data. We ascertained the pres-ence of comorbidities from the ICD-9 diagnosis codesassociated with ambulatory, emergency department, and inpa-tient care during the time period 12 months prior to and 12months following the first ULD dispensing. Comorbidities ofinterest included coronary heart disease, diabetes mellitus,dyslipidemia, hypertension, nephrolithiasis, peripheral arterialdisease, renal insufficiency and renal failure. A Charlsoncomorbidity score (the score does not include a gout diagno-sis) was ascertained based on a range of diagnoses and pro-cedures in the 12 months prior to the first ULD dispensing[19].

Medication usage was identified by determining dispensingsusing national drug codes (NDCs) for the following drugclasses: diuretics (thiazide, potassium sparing, loop and oth-ers), both cyclo-oxygenase selective and non-selective non-steroidal anti-inflammatory drugs (NSAIDs), colchicine, urico-suric drugs, xanthine oxidase inhibitors (allopurinol) and gluco-corticoids. Acute medications for gout were identified based



on dispensings of NSAIDs, colchicine and glucocorticoids inthe 1 to 12 months prior to the first ULD dispensing. Due tothe recommendations that patients receive prophylactic med-ications prior to ULD initiation, we looked separately at dis-pensings of NSAIDs, colchicine and glucocorticoids in the 30days prior to and including the date of the first ULD dispens-ing.

AnalysesThe characteristics of the study population were examined.The MPR was examined both by use of specific ULD agentsand by use of any ULDs, so that if patients switched agents,they could still be considered adherent. Adherence using theMPR (≥80%) based on initiated ULD (allopurinol vs probene-cid) was examined using the χ2 test. We then assessed corre-lates of non-adherence with use of any ULD. Logisticregression was used to estimate the strength of the associa-tion between patient characteristics and non-adherence. Vari-ables included in the models included age, gender, health careutilization (number of provider visits for gout, number of pro-vider visits for any diagnosis and hospitalizations prior to ULDinitiation), Charlson comorbidity score, use of diuretics, use ofacute gout medications in the 1 to 12 months prior to ULD ini-

tiation (NSAIDs, colchicine and glucocorticoids), use of acutegout medications in the 30 days prior to and including the dateof ULD initiation, and HMO. A backward elimination methodwas used to determine the variables to include in the multivar-iable models, including retaining all variables considered to bepotentially important. Variables with P values < 0.10 remainedin the final models. All analyses were run using SAS version9.1 (SAS Institute, Cary, NC, USA).

ResultsA total of 4,166 patients with a diagnosis of gout who were ini-tiated on a ULD during the study period. The mean age of thepopulation was 62 (± 14) years and 75% were male (Table 1).In the 12 months prior to and including the date of ULD initia-tion, the mean number of provider visits for gout was 1.67 (±1.62) with 288 (7%) patients having no in person encountersduring that period. After ULD initiation, the mean number ofprovider visits for gout was 1.73 (± 2.43). Comorbidities werecommon, including hypertension (70%), dyslipidemia (47%),coronary heart disease (24%), and diabetes (24%). More thanhalf of the patients were receiving diuretics.

Table 1

Baseline characteristics of patients initiating urate-lowering therapy

Characteristic Total population (N = 4,166)

Mean age, years (SD) 62 (14)

Gender, N (% male) 3,113 (75)

Number of provider visits for gout prior to ULD initiation, mean (SD)* 1.67 (1.62)

Number of physician visits for any diagnosis prior to ULD initiation, mean (SD)* 6.16 (5.81)

Hospitalization, N (%)* 782 (19)

Number of provider visits for gout after ULD initiation, mean (SD)† 1.73 (2.43)

Charlson comorbidity score, mean (SD) 1.06 (1.64)

Associated comorbidities, N (%):

Hypertension 2,904 (70)

Dyslipidemia 1,976 (47)

Coronary heart disease 1004 (24)

Diabetes mellitus 989 (24)

Renal insufficiency 816 (20)

Renal failure 629 (15)

Peripheral arterial disease 243 (6)

Nephrolithiasis 196 (5)

Medications associated with gout or difficulty treating gout, N (%):

Thiazide diuretics 1,569 (38)

All diuretics 2,259 (54)

*Over the 12 months prior to initiation of a ULD; †over the 12 months after initiation of a ULD.SD, standard deviation; ULD, urate-lowering drug.



The vast majority of patients initiated treatment with allopurinol(97%), with 3% receiving probenecid and less than 1% (onlyone patient) receiving sulfinpyrazone for urate lowering ther-apy (Table 2). The median MPR was 0.68 (interquartile range0.64) for allopurinol and 0.49 (interquartile range 0.70) forprobenecid. Adherence did not differ based on initiated ULD(allopurinol vs probenecid; P < 0.11) non-adherence (MPR <0.8) to any ULD during the first year of therapy occurred in56% of patients (Figure 1).

In the 1 to 12 months prior to ULD initiation, use of acute goutmedications was common (48% of patients were treated withNSAIDs, 21% colchicine and 18% glucocorticoids). Use ofacute gout medications in the 30 days prior to and includingthe date of ULD initiation (potentially dispensings for goutprophylaxis) occurred in the 64% of patients. NSAIDs and col-chicine were used in 37% and 29% of patients within the 30days prior to the date of ULD initiation, respectively. While glu-cocorticoids are not the typical medications used for goutprophylaxis, 16% of patients received these agents.

After controlling for health plan, in the adjusted analyses, fac-tors that increased the probability of non-adherence includedyounger age (odds ratio (OR) 2.43, 95% confidence interval(CI) 1.86 to 3.18 for ages <45 and OR 1.44, 95% CI 1.08 to1.93 for ages 45 to 49 compared with 75 and older), fewercomorbid conditions (OR 1.46, 95% CI 1.20 to 1.77 for Charl-son score of 0 compared with a score of 3 or more), no pro-vider visits for gout prior to ULD initiation (OR 1.28, 95% CI1.05 to 1.55 for no visits compared with three or more visits),and use of NSAIDs in the 1 to 12 months prior to ULD initiation(OR 1.15, 95% CI 1.00 to 1.31) (Table 3). Those aged 55 to

64 were significantly more likely to be adherent. The numberof physician visits prior to ULD initiation, hospitalizations anduse of prophylactic medications prior to ULD initiation werenot associated with non-adherence. As a sensitivity analysis,we re-ran the models excluding those with only one prescrip-tion for a ULD in case those patients were non-adherent dueto an adverse reaction. The strengths of the associations wereessentially the same.

DiscussionIn this study, we found poor adherence to newly-initiated ULDswas common in gout patients, with only 44% of the study pop-ulation achieving an MPR > 0.80 in the first year of therapy.Predictors of non-adherence included age less than 50 years,fewer comorbid conditions based on the Charlson score, noprovider visits specifically for gout care prior to ULD initiationand the use of NSAIDs in the year prior to ULD initiation. Thesefindings suggest that younger and healthier patients with goutmay be at particularly high risk for medication non-adherence,potentially due to a lack of experience in managing otherchronic conditions or seeking care. In addition, these patientsmay have a knowledge deficit in how and when to use theirmedications. We are currently conducting in-depth patientinterviews to explore these factors.

Our work is consistent with others showing adherence withULDs is generally poor, ranging from 44% to 64% of the studypopulations [8,11-13]. Previous studies also confirm our find-ing that younger age is associated with non-adherence[8,11,13]. Interestingly adherence was best in gout patients inthe middle age groups (ages 55 to 64). This finding has been

Table 2

Use of acute and chronic gout medication treatments in initiators of urate-lowering drugs (ULDs)

ULD Population, N (%)

Allopurinol 4,042 (97)

Probenecid 123 (3)

Sulfinpyrazone 1 (0)

Acute gout treatments prior to ULD initiation*:

NSAIDs 2,003 (48)

Colchicine 862 (21)

Glucocorticoids 742 (18)

Possible gout flare prophylaxis prior to ULD initiation†:

NSAIDs 1,554 (37)

Colchicine 1,189 (29)

Glucocorticoids 675 (16)

Total population N = 4,166.*Based on dispensings 1 to 12 months prior to ULD initiation; †based on dispensings 30 days prior to and including the date of ULD initiation.NSAID, non-steroidal anti-inflammatory drug.



seen in the medication management of other chronic condi-tions, such as diabetes [20].

This study adds to the body of knowledge regarding non-adherence in the management in gout. First of all, we evalu-ated adherence in new users of ULDs and included a sampleof gout patients that reflects the typical outpatient medicalpractice. In addition, we evaluated measures of gout care thathave not been previously examined including number of physi-cian encounters for gout prior to ULD initiation. Lack of pro-vider visits associated with a gout diagnosis prior to ULDinitiation was associated with non-adherence. This suggests aface-to-face meeting focused on gout is needed to discuss therationale and goals of medication treatment of gout. Interest-ingly, we found that 7% of our population had no encountersprior to initiating ULDs. We surmise this occurred whenpatients called the physician's office for a prescription beforea visit could occur. Since these patients may not be new usersbut rather patients with a long gap since their last prescription,we conducted a subanalysis excluding those patients from themodel. Non-adherence was still associated with younger ageand fewer comorbid conditions.

Use of NSAIDs, a class of medications used to treat acutegout, prior to ULD initiation was also significantly associatedwith non-adherence and the relationship persisted even whenwe controlled for use of prophylactic medications prior to ULDinitiation. This suggests that patients with likely inadequatelycontrolled gout prior to ULD initiation (reflecting the need forprescription NSAIDs) are less adherent. This finding was con-trary to our a priori hypothesis that active gout would be linkedto higher adherence. Interestingly, lack of prophylactic medi-cations (NSAIDs or colchicine dispensed in the 30 days priorto and including the date of ULD initiation) was not associatedwith non-adherence.

These results have practical implications for clinicians. Whilemany providers assume patients with painful arthritic condi-tions are adherent to their medications, our work has shownthat this is not the case. Providers and health care systems

may wish to identify patients at high risk for non-adherencebased on the factors identified in this study. In those high-risksubsets of the gout population, providers could emphasize therationale and benefits of ULDs in the treatment of gout and theconsequences of non-adherence. Of note, post hoc analysesrevealed that fewer number of provider visits for gout followingULD initiation were also associated with greater non-adher-ence both in adjusted and non-adjusted analyses. In light ofthese data, providers may wish to automatically schedule fol-low-up encounters after ULD initiation to review clinical statusand to encourage medication adherence.

One of the strengths of this study is the sample inclusion cri-terion of a diagnosis of gout, which other studies have not fea-tured. While this does not eliminate misclassification bias, itdoes reduce the likelihood that patients were receiving ULDsfor the treatment of asymptomatic hyperuricemia, in whichtreatment recommendations and goals may differ from thestandard lifelong treatment of gout with ULDs [4,21]. We alsoincluded data from two health delivery systems in differentgeographic regions, which reduced the influence of regionalprescribing practices on our results and increased generaliza-bility. Additionally, we were able to explore the relationshipbetween gout-related care, such as provider visits for gout,use of acute gout medications prior to ULD initiation and useof potentially prophylactic medications. Lastly, given the studypopulation had pharmacy benefits and ULDs are relativelyinexpensive, we minimized the likelihood that financial con-straints influenced adherence.

This study has several limitations. We conducted a retrospec-tive analysis of pharmacy dispensings to measure adherence.Therefore, we could not confirm whether patients actually tookthe medications that they had filled. In addition, we did nothave access to the patients or the clinical records to ascertainthe reasons for gaps in therapy. We could not determinewhether patients became non-adherent due to adverse reac-tions, at the suggestion of their provider, or secondary to otherfactors. However, it does seem less likely that non-adherencewas due to an adverse reaction since when we re-ran the anal-yses excluding those who filled only one prescription thestrengths of the associations were essentially the same.

Additionally, due to the limitations of pharmacy dispensingrecords we were not able to confirm the indication for NSAIDsand colchicine dispensed within the 30 days prior to andincluding the date of the first ULD dispensing. Patients mayhave also obtained over the counter NSAIDs that would not becaptured by this study. However, since all the patients hadpharmacy benefits, there is a financial incentive to obtain a pre-scription NSAID rather than take numerous over the counterpills to replicate the prescription dosage.

We did not have access to laboratory results and thus wereunable to assess the impact of ULD adherence on uric acid

Figure 1

The distribution of the medication possession ratio (MPR) for any urate-lowering drug (ULD) useThe distribution of the medication possession ratio (MPR) for any urate-lowering drug (ULD) use. The distribution of the study population in terms of MPR for any ULD use was examined.



levels. We also did not have access to the specialty of the ULDprescriber and thus could not examine whether adherencewas influenced by provider specialty, specifically whetherpatients cared for by rheumatologists were more adherent. Inaddition, we were unable to determine definitely if visits asso-ciated with a diagnosis of gout were for acute gout flares ver-sus routine follow-up appointments. Therefore, we could notdirectly determine the relationship between adherence andthe frequency of gout attacks. Lastly, the population was over-whelming Caucasian, and thus we could not examine whetherpatient race and ethnicity influenced adherence.

ConclusionsNon-adherence with ULDs for the treatment of chronic goutoccurred in the majority of the study population. While furtherresearch is needed to assess the clinical and economic con-sequences of non-adherence, it is likely the patients did notachieve the recommended reduction in serum urate levels andthus are at risk for future gout flares, nephrolithiasis and boneyerosions. Providers should be aware of the magnitude of theproblem of non-adherence with ULDs, and counsel patientson the need for ULD adherence.

Competing interestsThe authors declare that they have no competing interests.

Table 3

Adjusted logistic regression model for non-adherence (medication possession ratio (MPR) < 0.80)*

Variable† Adjusted odds ratio (95% confidence interval)

Sociodemographic:

Gender, female 1.03 (0.88 to 1.19)

Age

<45 2.43 (1.86 to 3.18)

45 to 49 1.45 (1.08 to 1.93)

50 to 54 1.09 (0.86 to 1.39)

55 to 59 0.78 (0.61 to 0.99)

60 to 64 0.75 (0.59 to 0.96)

65 to 69 0.84 (0.67 to 1.04)

70 to 74 0.83 (0.67 to 1.02)

75 + 1.00

Health status:

Charlson comorbidity score

0 1.46 (1.20 to 1.77)

1 1.21 (0.98 to 1.51)

2 1.20 (0.94 to 1.53)

3 or more 1.00

Gout care:

Number of provider visits for gout prior to ULD initiation

0 1.28 (1.05 to 1.55)

1 1.09 (0.92 to 1.30)

2 1.00 (0.83 to 1.21)

3 or more 1.00

Use of acute gout meds 1 to 12 months prior to urate-lowering drug initiation

NSAIDs 1.15 (1.00 to 1.31)

*A backward elimination method was used retaining all variables considered to be potentially important. Variables with P values < 0.10 remained in the final models. The Hosmer-Lemeshow goodness of fit had a P value of 0.70; †model after controlling for health plan.NSAID, non-steroidal anti-inflammatory drug; ULD, urate-lowering drug.



Authors' contributionsAll authors made substantive intellectual contributions to thisstudy to qualify as authors. LH was involved in the conceptionand design of this project, analysis and interpretation of thedata, and drafting of this article. SA was involved in the designof this project, data acquisition and analysis, interpretation ofthe data, and critiquing of drafts of this article. BB wasinvolved in the design of this project, analysis and interpreta-tion of the data, and critiquing of drafts of this article. MR wasinvolved in data acquisition, interpretation of the data and cri-tiquing of drafts of this article. HF was involved in the analysisof data from this study and interpretation and presentation ofresults. RY was involved in the interpretation of the data, anddrafting of this article. IO was involved in the conception anddesign of this project, analysis and interpretation of the data,and critiquing of drafts of this article. All authors read andapproved the final manuscript.

AcknowledgementsLRH was supported by Grant Number K23AR053856 from the National Institute of Arthritis and Musculoskeletal and Skin Diseases. The content is solely the responsibility of the authors and does not necessarily rep-resent the official views of the National Institute of Arthritis and Muscu-loskeletal and Skin Diseases or the National Institutes of Health.

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